BACKGROUND: Low cardiorespiratory fitness (CRF) increases risk of all-cause mortality and cardiovascular events. Periodic CRF assessment can have an important preventive function.
OBJECTIVE: To develop a protocol-free method to estimate CRF in daily life based on heart rate (HR) and body acceleration measurements.
METHODS: Acceleration and HR data were collected from 37 subjects (M=49%) while performing a standardized laboratory activity protocol (sitting, walking, running, cycling) and during a 5-days free-living monitoring period. CRF was determined by oxygen uptake (VO2max) during maximal exercise testing. A doubly-labeled water validated equation was used to predict total energy expenditure (TEE) from acceleration data. A fitness index was defined as the ratio between TEE and HR (TEE-pulse). Activity recognition techniques were used to process acceleration features and classify sedentary, ambulatory and other activity types. Regression equations based on TEE-pulse data from each activity type were developed to predict VO2max.
RESULTS: TEE-pulse measured within each activity type of the laboratory protocol was highly correlated to VO2max (r from 0.74 to 0.91). Averaging the outcome of each activity-type specific equation based on TEE-pulse from the laboratory data led to accurate estimates of VO2max (RMSE: 300.0 mlO2/min or 10%). The difference between laboratory and free-living determined TEE-pulse was 3.7 ± 11% (r =0.85). The prediction method preserved the prediction accuracy when applied to free-living data (RMSE: 367 mlO2/min or 12%).
CONCLUSIONS: Measurements of body acceleration and HR can be used to predict VO2max in daily life. Activity-specific prediction equations are needed to achieve highly accurate estimates of CRF.